Computer-implemented business intelligence (BI) applications have been developed to facilitate discovery of knowledge (e.g., a business fact) that may assist a business in reaching a business goal. With more particularity, a user of a business intelligence application can formulate a query that is to be executed over data pertaining to a particular business. Conventionally, the data pertaining to the business is structured as at least one relational database that comprises at least one two-dimensional table.
While conventional BI applications provide an adequate interface to assist users in acquiring business knowledge when the data pertaining to the business is structured as relational databases, conventional business intelligence applications are not as well-suited for discovering business knowledge from a multidimensional data structure (e.g., a data cube, sometime referred to as a “hypercube”). In an example, when data pertaining to a business is structured as a data cube, a user who wishes to obtain business knowledge by querying the data cube must have a priori knowledge of the contents of the cube. Further, the user must be familiar with a query language that can be used to execute queries over the data cube. Moreover, the user must have knowledge of slices and/or dices of the data cube that are of interest when formulating the query. Thus, the user must formulate a final query, which may not result in presentment of desired business knowledge.